using facial coding technology to capture emotions on mobile - millward brown
TRANSCRIPT
Proudly supported by Kantar, the Leader in Mobile Marketing Research
January 30-31, 2013
Kuala Lumpur, Malaysia
Asia-Pacific Edition 2013 WWW.MRMW.NET
Organized by
TM
Thank you to our sponsors!
Title Sponsor Platinum Sponsor Gold Sponsors
Silver Sponsor Exhibitor Networking Evening Sponsor Networking Break Sponsor
Association Partners
Media Partners
Measuring emotions thru facial expressions
• Using mobile in field
• Getting desired outcomes
Adding insights to Ad testing
Possibilities
Agenda
2
What did we do
• Pilot study in India
• 300 participants shown 6 beverage ads each in two cities: Hyderabad and Delhi
• Interviewers showed ads to respondents on a phone
• Recorded the face video of respondents synched with ad playing
• Analysis of face expressions to provide moment by moment emotional feedback
Objectives
• Feasibility of using mobile to capture emotions
• Feasibility of obtaining sensible data using this technology
• Feasibility of providing additional insights on advertising
Feasibility of using mobile to capture emotions
Less than 50% of the videos were usable initially.
Iterative training of interviewers to ensure that we got better quality videos.
Lighting and overexposure
Full face in frame not visible
Non-frontal, multiple faces
Feasibility of using mobile to capture emotions
Iterative training of interviewers ensured that we finally got good quality videos.
1. Simple rules: Place the device at arm’s length from respondent
2. Higher resolution/wider angle cameras for better results.
3. Define a minimal acceptable threshold: 40% of frames must be discernible.
Feasibility of obtaining sensible data
• Validated that the participants where “emoting” while watching the ads on a mobile device, and we are able to accurately capture these facial expressions.
• Range of facial expressions observed in response to the ads - enjoyment to surprise & confusion
Providing additional insights on advertising
We compared the results from the facial expressions with our advertising testing outcomes for ads.
We were able to find out insights which helped sharpen our understanding of how the ads were working.
Sprite – Delhi Facial expressions confirmed the key aspects liked in the ad were causing most smiles, the
extent of emotions displayed can help prioritise between different parts.
The scene in the middle did not evoke a strong response in
facial expressions as the last scene of ‘boy being successful
in selling his excuse for staring at the other girl’.
Smile
Consumers fail to understand the role of
professor/theme of the Ad in Link – this is a point of
confusion captured from facial expressions
Confusion
Sprite – Hyderabad
Valence
Again, in Hyderabad we could see that it is the
scene where the boy is successful in selling his
excuse for ogling at the other girl in front of his
girlfriend which gets the highest emotional payoff
Here too, the appearance of the Professor of
Freshology is clearly creating confusion for
the consumers
Confusion
Coke - Delhi
Smile Confusion
In Delhi, respondents smile the most when the teacher is
shown holding the Coke bottle that Imran Khan meant to pass
on to the girl in the classroom
The Sardar & Parrot scenes also evokes smiles
Sequences in quick succession create confusion
Coke - Delhi
Peak valence for Delhi
respondents watching the
Coke ad occurs when the
parrot also shakes in a
manner similar to the rest
of the characters in the ad,
this not only evokes smiles,
but also resolves confusion
One of the reasons why we
felt the brand had a good
recall in Link was due to
the product being right
there when the most
emotionally positive
moment in the ad occurs
Valence
Facial expressions helped pinpoint the exact moments which created positive payoff – both
through evoking smiles and resolving confusion
Valence
Coke - Hyderabad We can see the sharpness with which the key moments which cause a response come
through compared to the more aggregate responses in Link
Confusion
In Hyderabad, valence peaks at the
culmination of the teacher sequence
The parrot scene
continues to evoke a
sharp positive response
in Hyderabad as well
Multiple sequences shown in quick succession
create confusion among the consumers
7 Up - Delhi
Confusion
The role of the brand in the second half of the
ad is unclear leading to confusion
7 Up
Smile
Hyderabad
Smile
Delhi
The emotions in the two markets peak at different points of the narrative
RECAP: Using Emotions to Add Value to Advertising testing
Facial Coding data Analysed with Link to provide additional insights
Facial coding dashboards Lumi Technology: Showing Ads & Capture Face Video on Mobile
Affectiva Facial Coding Analysis
POSSIBILITIES
• The technology enables us to use it with advertising testing at various stages:
• Capturing consumers’ emotions when they are watching an ad
remotely on their mobile devices
• Capture emotions in tracking studies & evaluate response over time
Thank you to our sponsors!
Title Sponsor Platinum Sponsor Gold Sponsors
Silver Sponsor Exhibitor Networking Evening Sponsor Networking Break Sponsor
Association Partners
Media Partners